Browse Articles

Pancreatic Adenocarcinoma: An Analysis of Drug Therapy Options through Interaction Maps and Graph Theory

Gupta et al. | Feb 04, 2014

Pancreatic Adenocarcinoma: An Analysis of Drug Therapy Options through Interaction Maps and Graph Theory

Cancer is often caused by improper function of a few proteins, and sometimes it takes only a few proteins to malfunction to cause drastic changes in cells. Here the authors look at the genes that were mutated in patients with a type of pancreatic cancer to identify proteins that are important in causing cancer. They also determined which proteins currently lack effective treatment, and suggest that certain proteins (named KRAS, CDKN2A, and RBBP8) are the most important candidates for developing drugs to treat pancreatic cancer.

Read More...

The effects of cochineal and Allura Red AC dyes on Escherichia coli and Bacillus coagulans growth

Palmatier et al. | Jun 29, 2025

The effects of cochineal and Allura Red AC dyes on <i>Escherichia coli</i> and <i>Bacillus coagulans</i> growth

Here the authors aimed to compare the effects of artificial Allura Red AC dye and natural cochineal dye on the growth of Escherichia coli and Bacillus coagulans bacteria. Their research found that only Allura Red AC dye significantly affected bacterial growth, specifically amplifying E. coli growth. Based on their results, they suggest that Allura Red AC dye may increase the growth of E. coli bacteria within the human gut.

Read More...

Validating DTAPs with large language models: A novel approach to drug repurposing

Curtis et al. | Mar 02, 2025

Validating DTAPs with large language models: A novel approach to drug repurposing
Image credit: Growtika

Here, the authors investigated the integration of large language models (LLMs) with drug target affinity predictors (DTAPs) to improve drug repurposing, demonstrating a significant increase in prediction accuracy, particularly with GPT-4, for psychotropic drugs and the sigma-1 receptor. This novel approach offers to potentially accelerate and reduce the cost of drug discovery by efficiently identifying new therapeutic uses for existing drugs.

Read More...

Forecasting air quality index: A statistical machine learning and deep learning approach

Pasula et al. | Feb 17, 2025

Forecasting air quality index: A statistical machine learning and deep learning approach
Image credit: Amir Hosseini

Here the authors investigated air quality forecasting in India, comparing traditional time series models like SARIMA with deep learning models like LSTM. The research found that SARIMA models, which capture seasonal variations, outperform LSTM models in predicting Air Quality Index (AQI) levels across multiple Indian cities, supporting the hypothesis that simpler models can be more effective for this specific task.

Read More...

Changing the surface properties of the backside of a silicon wafer to repel oil and prevent particle binding

Choi et al. | Feb 14, 2025

Changing the surface properties of the backside of a silicon wafer to repel oil and prevent particle binding

Wafers, essential in microchip production, can develop issues like leveling problems and wafer slip due to the formation of silanol bonds on their backside, which attract silica particles and oil. Authors tested addressing this issue with a coating of [acetoxy(polyethyleneoxy)propyl]triethoxysilane (APTS) applied to the wafer’s backside, preventing particle binding and oil adherence.

Read More...